The modern communications era has brought about a tremendous expansion of wireline and wireless networks. Computer networks, television networks, and telephony networks are experiencing an unprecedented technological expansion, fueled by consumer demand. Wireless and mobile networking technologies have addressed related consumer demands, while providing more flexibility and immediacy of information transfer.
Current and future networking technologies continue to facilitate ease of information transfer and convenience to users. Due to the now ubiquitous nature of electronic communication devices, people of all ages and education levels are utilizing electronic devices to communicate with other individuals or contacts, receive services and/or share information, media and other content. One area in which there is a demand to increase convenience to users relates to improving the ability of a communication device to effectively perform face detection and recognition.
In this regard, face detection and recognition is becoming an increasingly more important technology. For example, face detection may be useful in biometrics, user interface, and other areas such as creating context for accessing communities in the mobile domain. Face detection may also be important going forward in relation to initiatives such as metadata standardization.
Although face detection techniques continue to improve, many current methods require either a high computation capability (e.g., statistical methods of detecting faces by scanning images in a traversing way on multiple scales). Furthermore, some statistical face detection mechanisms have degraded performance for multi-view face detection in relation to front face detection. As another complicating issue, in face recognition (FR), the performance of face recognition may improve as the number of faces of images associated with various conditions increases and are stored in a database. This may be achieved by adding and tagging more faces of the same individuals as they are captured by a device and storing the images of the faces in the database. One of the various conditions associated with images of faces may relate to different lighting conditions of the images. In this regard, the accuracy of current methods in performing face recognition may drop approximately 50% when there are lighting variations in images. For instance, it may be difficult for current methods to detect that a face of an individual in an image that is not well lit (e.g., a dark image) relates to a face of the same individual in another (e.g., newly captured) image that is well lit (e.g., a bright image). Given that there may not be images of the same individual associated with different lighting conditions in a database, it may be difficult for current methods to detect and recognize an image of a face of the individual in an instance in which the corresponding image has a different lighting condition than the image of the face of the individual stored in the database.
Additionally, many current methods suffer from limited face detection performance associated with relatively high false alarms of face detection. The false alarms may relate to a region of an image which is not a face being detected as a face. Accordingly, the tendency for developing devices with continued increases in their capacity to create content, store content and/or receive content relatively quickly upon request, the trend toward electronic devices (e.g., mobile electronic devices such as mobile phones) becoming increasingly ubiquitous in the modern world, and the drive for continued improvements in interface and access mechanisms to unlock the capabilities of such devices, may make it desirable to provide further improvements in the area of face detection and recognition.
In this regard, in view of the foregoing drawbacks, it may be beneficial to provide an efficient and reliable mechanism for improving the accuracy in performing face recognition corresponding to images associated with various illumination conditions and for reducing false detections of faces.